Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks. - Sitao Luan; Mingde Zhao 001; Xiao-Wen Chang; Doina Precup (NeurIPS, 2019)

META-Learning State-based Eligibility Traces for More Sample-Efficient Policy Evaluation. - Mingde Zhao 001; Sitao Luan; Ian Porada; Xiao-Wen Chang; Doina Precup (AAMAS, 2020)

META-Learning Eligibility Traces for More Sample Efficient Temporal Difference Learning. - Mingde Zhao 001 (CoRR, 2020)

Complete the Missing Half: Augmenting Aggregation Filtering with Diversification for Graph Convolutional Networks. - Sitao Luan; Mingde Zhao 001; Chenqing Hua; Xiao-Wen Chang; Doina Precup (CoRR, 2020)

A Consciousness-Inspired Planning Agent for Model-Based Reinforcement Learning. - Mingde Zhao 001; Zhen Liu 019; Sitao Luan; Shuyuan Zhang; Doina Precup; Yoshua Bengio (NeurIPS, 2021)

Is Heterophily A Real Nightmare For Graph Neural Networks To Do Node Classification? - Sitao Luan; Chenqing Hua; Qincheng Lu; Jiaqi Zhu; Mingde Zhao 001; Shuyuan Zhang; Xiao-Wen Chang; Doina Precup (CoRR, 2021)

Revisiting Heterophily For Graph Neural Networks. - Sitao Luan; Chenqing Hua; Qincheng Lu; Jiaqi Zhu; Mingde Zhao 001; Shuyuan Zhang; Xiao-Wen Chang; Doina Precup (NeurIPS, 2022)

Temporal abstractions-augmented temporally contrastive learning: An alternative to the Laplacian in RL. - Akram Erraqabi; Marlos C. Machado; Mingde Zhao 001; Sainbayar Sukhbaatar; Alessandro Lazaric; Ludovic Denoyer; Yoshua Bengio (UAI, 2022)

Complete the Missing Half: Augmenting Aggregation Filtering with Diversification for Graph Convolutional Neural Networks. - Sitao Luan; Mingde Zhao 001; Chenqing Hua; Xiao-Wen Chang; Doina Precup (CoRR, 2022)

Training Matters: Unlocking Potentials of Deeper Graph Convolutional Neural Networks. - Sitao Luan; Mingde Zhao 001; Xiao-Wen Chang; Doina Precup (COMPLEX NETWORKS (1), 2023)

Combining Spatial and Temporal Abstraction in Planning for Better Generalization. - Mingde Zhao 001; Safa Alver; Harm van Seijen; Romain Laroche; Doina Precup; Yoshua Bengio (CoRR, 2023)

Consciousness-Inspired Spatio-Temporal Abstractions for Better Generalization in Reinforcement Learning. - Harry Zhao 001; Safa Alver; Harm van Seijen; Romain Laroche; Doina Precup; Yoshua Bengio (ICLR, 2024)

Identifying and Addressing Delusions for Target-Directed Decision-Making. - Mingde Zhao 001; Tristan Sylvain; Doina Precup; Yoshua Bengio (CoRR, 2024)